1. Field of the Invention
This invention relates to methods of detecting and analyzing patterns of cytosine methylation in genomic DNA.
2. Description of Related Art
Throughout development, cells and tissues differentiate and change as an organism ages. These changes include alterations to telomeres, accumulation of DNA mutations, decay of cellular and organ structures, and changes in gene expression (see, e.g. Goyns M H (2002) Mech Ageing Dev 123: 791-799). Both differentiation of tissues and aging effects are at least partially caused by chemical modifications of the genome, such as DNA methylation. In particular, the genomic DNA of higher eukaryotes contains modified nucleosides including 5-methyl cytosines. This modification is usually found as part of the dinucleotide CpG.
DNA methylation is an epigenetic determinant of gene expression. Patterns of CpG methylation are heritable, tissue specific, and correlate with gene expression. The consequence of methylation is usually gene silencing. DNA methylation also correlates with other cellular processes including embryonic development, chromatin structure, genomic imprinting, somatic X-chromosome inactivation in females, inhibition of transcription and transposition of foreign DNA and timing of DNA replication. When a gene is highly methylated it is less likely to be expressed. Thus the identification of sites in the genome containing 5-meC is important in understanding cell-type specific programs of gene expression and how gene expression profiles are altered during both normal development and diseases such as cancer. Mapping of DNA methylation patterns is important for understanding diverse biological processes such as the regulation of imprinted genes, X chromosome inactivation, and tumor suppressor gene silencing in human cancers.
Several studies have investigated the epigenetic state of a small number of selected genes or CpG islands in subjects of varying age or have measured the global changes in DNA methylation with increasing age (see, e.g. Boks M P, et al. (2009) PLoS One 4: e6767; and Fraga M F, et al. (2005) Proc Natl Acad Sci USA 102: 10604-10609). Recently, unbiased genome-wide studies have documented age effects on DNA methylation in cultured cells, mice, and humans (see, e.g. see, e.g. Bork S, et al. (2009) Aging Cell 9: 54-63; Maegawa S, et al. (2010) Genome Res 20: 332-340; and Teschendorff A E, et al. (2010) Genome Res 20: 440-446; Gronniger E, et al. (2010) PLoS Genet 6: e1000971; Rakyan V K, et al. (2010) Genome Res 20: 434-439). In these reports, the subject's were of a limited age range, and the continuity of the age related changes was not defined. Consequently, estimating the age of an individual by observing methylation patterns in their genomic DNA has not been possible.
Methods for estimating the age of an individual by observing methylation patterns in genomic DNA obtained from a biological sample have a number of applications. For example, the characterization of biological materials is one of the most important methods for identification of individuals in forensic medicine and/or in criminal investigations (see, e.g. van Oorschot et al., Investigative Genetics 2010, 1:14; and Thompson et al., Methods Mol Biol. 2012; 830:3-16). When analyzing biological materials found at a crime scene, common procedures include DNA analysis techniques such as DNA fingerprinting to specifically identify the individual from which the biological material was derived. New DNA analysis techniques, for example those that can be used to predict an approximate age of an individual, are desirable.